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The Efficient Markets Hypothesis and Modern Finance with Nobel Prize Winner Eugene Fama · The Capitalism and Freedom in the Twenty-First Century Podcast

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[MUSIC]
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>> Jon Hartley: This is the Capitalism and Freedom in the 21st Century podcast,
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an official podcast of Hoover Institution Economic Policy Working Group where we
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talk about economics, markets and public policy.
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I'm Jon Hartley, your host today.
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My guest is Eugene Fonda, who is a professor of finance at the University of
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Chicago at Booth School of Business,
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is widely regarded as the father of modern finance, as his research has really,
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truly built the foundation of the field of financial economics as we know it today,
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for which he was awarded the Nobel Prize in economic sciences in 2013.
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Welcome, Gene.
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>> Eugene Fama: Thank you, >> Jon Hartley: Gene.
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I want to first get into your early life.
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You were born in Boston, you grew up in the Boston area.
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All your grandparents were Italian immigrants from Italy, as I understand it.
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And my understanding is that you're actually named after one of
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the Pope Eugenes.
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You are an athletic all star at the Malden Catholic High School,
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you're in their athletic hall of fame.
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And it's in the Boston area, that's Middlesex County.
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You study Romance Languages as an undergraduate at Tufts.
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How did you get interested in finance and decide to do an MBA and
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PhD at University of Chicago and
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arguably become the greatest financial economist ever?
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>> Eugene Fama: Well, my initial intent was to be a sports coach and
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a French teacher.
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So I took Romance Languages there my first year, two years at Tufts, and
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I was getting bored with it.
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So I took an economics course and I loved it and the professors loved me.
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They were reading my exams to the class, so I immediately switched into colleague.
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And I was close as I could in my last two years.
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Then when it came time to, I said,
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I think I want to go to graduate school and get a Ph.D.
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And my professors, who were all Harvard graduates, I said, I don't wanna go to
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an economics department, I wanna go to a business school.
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And they were all Harvard graduates.
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And they said, well, don't go to Harvard, don't go to the University of Chicago.
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They have more of an academic orientation there.
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And so I applied, and I never heard back from them.
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And March came along and not having heard back, I called and
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the Dean of Students answered the phone.
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The student doesn't even have a phone now because he's too important, but
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answered the phone and talked to me for a while.
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He said, you know, I got some bad news for you, and
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I don't have any record of your application.
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But he said, what kind of grades do you have?
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And I said, well, basically all A's.
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And he said, well, we just happened to have a scholarship for
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somebody from Tufts.
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Do you want it and that's how I ended up at the University of Chicago.
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>> Jon Hartley: Wow, that's amazing.
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And I mean, in terms of your sports interests, it's wonderful.
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I know you play a lot of golf and
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you're still playing a lot of golf over the years.
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So it's great to see that you maintain some of
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that initial interest in sports as well.
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You spent your entire career as both a graduate student and
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professor at the University of Chicago.
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And you arrived there in the 1960s, and
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there were a lot of other folks who were there at that time.
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I mean, it was truly, as I understand, a foundational period for
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financial economics as a field.
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There was so little done at that point in time.
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I mean, my sense is that, you know, Markowitz,
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Harry Markowitz had just written down the mean variance model in the 50s.
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Things like the CAPM were sort of just being written down by folks
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like Bill Sharp.
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But at Chicago, you had folks like Martin Miller,
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Harry Roberts, they're your advisors.
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You had folks like Myron Scholz, who you advised, and
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other folks like Dick Roll, many, many others who are really
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foundational to financial economics and developing the field as it was so early.
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What was it like doing financial economics research at that time?
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Obviously personal computers didn't really even exist at that point in time.
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How you would a young Gene Fama even do financial economics research in the 1960s?
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I mean, what sorts of tools were you using and
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what sorts of tools were being developed?
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>> Eugene Fama: Well, I got into it because Harry Roberts,
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who was a statistics professor who I really admired,
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and Merton Miller, who was my main advisor.
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The two of them who my advisors, they were both interested in the work that was going
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on in describing price formation, trying to say something intelligent about it.
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And in there, people working in it.
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There were some at MIT, some in Chicago.
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They were kind of fumbling around the edges.
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They had no clear conception of what they were trying to do.
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So they were doing tests and saying these are tests of market efficiencies, but
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they're basically said efficiency applies, that prices are in walk.
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But that, that was a very crude way of, of approaching stuff.
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So basically what I did was I started working on that because I knew it was
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a quick way to get a PhD because everybody there was interested in it.
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And I had two kids at the time and I had to get out quickly.
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So I said, I started working, and then I've been doing it, I guess more or
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less ever since.
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But basically what I added to it was a statement that what you're missing here is
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that you have to have some statement about what equilibrium looks like in this world.
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So what are expected returns that had been totally left out of the picture?
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That's what I call the joint hypothesis problem.
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You have to say something about expected returns in order to say something
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about market efficiency.
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That really set the world into thinking in that direction, and research exploded.
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So I say to everybody, well, I was there at the right time.
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That's what it comes down to.
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Nothing had been done.
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So everything you did was new, it was really very easy.
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PhD students now have it very difficult because they have lots of stuff they have
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to learn, and then they make a little play on the wrinkle, adding a wrinkle to it.
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Whereas when we were doing it early on, it was like shining fish in a barrel,
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everything had better.
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>> Jon Hartley: So, well,
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now we're staying on the shoulders of giants like yourself.
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And it's amazing as somebody who's a young researcher.
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Yeah, it's amazing to imagine just what it would be like sitting in a room with any
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of those people talking about financial economics and
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what hadn't been written down yet.
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It's really quite amazing.
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And I know, you know, before I get into sort of your body of work here,
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I know just another amazing story, you know, University of Chicago,
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that people, some people might know or might not appreciate,
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is that the University of Chicago Booth School of Business gets its namesake
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ultimately from, in part, your thinking.
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You know, two of your students, David Booth and Rex Sinquefield,
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they were students of yours in the 1980s, and
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they left to start one of the first index fund businesses and
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brought you in as part of that effort.
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And ultimately, because of that success,
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David Booth made a very big contribution to the University of Chicago.
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And hence, that's where it got its name from.
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So the Booth School of Business name, in part is thanks to your ideas.
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What was that like?
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And could you explain to me a little bit about, you know,
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what the early days of dimensional point advisor, DFA, which was founded by.
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Field and did with your students.
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What was that like?
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And, and, you know, being part of it since.
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>> Eugene Fama: Well, Booth was my research assistant, my teaching assistant,
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when at the same time that Rex was in the class, so
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advanced class for PhD students and ambitious MBA students.
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And Rex took it all to Hyde, went off to American national instead of
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really the first index slides based on what he learned in the course and David,
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who was my research assistant and my teaching assistant, so he came to me and
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finally after three years said, I see what you do for research.
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I've been helping you do it, and I don't want to do it.
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I want to go out and work.
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So I called John Macquan at Wells Fargo and got him a job, and he went off
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there and then 10 years later he called me, he said he wanted to start a business.
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And what he wanted to do was he had read all the recent work and there was a lot of
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work at that time about how small stocks tend to have high average returns.
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And he said he wanted to start a small stock fund because none existed for
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institutional investors at that time.
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They had stayed away from that, and he wanted to start one.
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So that's how dimensional fund advisors came about and he said,
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I want you to be involved.
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And I said, well, I don't target my research at commercial products and
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he said, well, you do what you do.
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We'll figure out if we can use any of it.
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And that's basically the relation we've had with them forever.
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First me and then me and Ken French after a while.
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>> [COUGH] >> Jon Hartley: It's amazing.
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I mean, it's amazing how applicable financial economics is in the real world.
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And I remember you saying in the past that the future economics is
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the most successful area of economics.
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And I think if we're measuring success by application, I think that almost certainly
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in the sort of magnitude of impact, I think that's almost certainly the case.
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I can't imagine how finance things like factors, things like the cap and
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someone who worked in finance, Goldman Sachs asset management for
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five years, all these ideas like cap and beta or market beta.
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I mean, these things are just so fundamental to the practice of finance.
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And what's amazing is, you know, you've done so much of, so
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much work on this topic, and you've been so early to so many topics.
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I think my mind,
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you're one of the few people I think that would deserve two Nobel Prizes.
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And just to list a few of these ideas like fat tails, were writing about fat tails,
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the distribution of stock prices in your PhD thesis in the 1960s,
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the idea that stocks can have extreme events.
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And that was roughly around the time when Black Swan author
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Nassim Taylor was just born, you've written about event studies.
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>> Eugene Fama: You're missing was the one who had that idea about the fat tails.
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He said everything in the world was fat tails, so.
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>> Jon Hartley: Wow, that's amazing I applied even earlier.
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>> Eugene Fama: I did not invent that concept, SOX.
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I got it, I got it from him.
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I applied it.
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But it was, that was his idea, basically efficient markets,
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I'll take credit for it, but not fat deals.
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>> Jon Hartley: We'll get to efficient markets in a minute here.
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But you wanna think about event studies and event studies just in general,
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causal inference is swept economics as a discipline since the 1990s.
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But you were there in the 1960s with Fama, Fisher, Jensen and Roll,
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1969, which sort of laid the groundwork for doing event studies,
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I think about the forward premium puzzle and carry trades.
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In 1984, you wrote a paper about the forward premium puzzle.
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You know, the idea that, you know,
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currencies aren't necessarily obeying the uncovered interest rate parity, where,
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you know, the higher interest rate currencies are selling that they're not
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actually selling off, as sort of theory would predict.
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And then you've done also a lot of amazing work in sort of the corporate finance,
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organizational economics theory, the firm kind of area too and
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a lot of amazing things like the stock market effects of buybacks, dividend
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announcements agency problems theory, the firm, the idea that competitive
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markets naturally sort of align with managerial and shareholder interests.
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I'm just curious.
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I mean, one, lots of these, all these greatest hits.
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Many of these greatest hits are covered in a book called the Fondal Portfolio,
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which is a great collection of your work that's edited by John Cochrane and
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Tobias Moskowitz as well.
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But I'm curious, taking a step back,
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how would you describe the overall theme of your work?
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What in your mind ties everything together?
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Is it risk based asset pricing?
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Diffusion of information, competition?
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Dare I say efficient markets?
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>> Eugene Fama: Well, efficient markets is one but the logic underlying efficient
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markets would have a lot to do with the way, for example, Jensen and
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I looked at and his markets more generally in terms of organizational markets and
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how they form and competition pushes them in a particular direction.
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So the idea of competition kind of determining how economies work and
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a lots of different dimensions that's basically the foundation
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of efficient markets and the foundation of lots of other stuff that I've done.
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But basically I think I had a knack of going into areas where very little had
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been done and coming up with simple stuff that people related to.
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So I've always said that one of my best talents is writing in a very simple way so
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the maximum number of people can understand it.
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And I teach that to my students, some of them follow it, some of them don't.
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But I still think it's a good rule to go by in research.
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But anyway, I think I was in part lucky and
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in fact I had a pretty good nose for it, what good topics were.
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>> Jon Hartley: Amazing, to say the least.
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So I want to start by getting into efficient markets here and dive into it.
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So there's this joint hypothesis problem which you talked about in your
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Nobel Prize lecture.
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And that's been sort of a big theme of, I think, a lot of your work.
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What led you to write your famous 1970 article,
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Efficient Capital Markets, and sort of what began this lifelong foray into
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being sort of a defender of the efficient markets hypothesis that says that
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stock markets are pricing information quickly, was Mandelbrot at all
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an influence here nd what was your relationship with Mandelbrot?
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I'm curious.
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>> Eugene Fama: No, I had a good relationship with him.
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He wasn't, he wasn't the motivator for that.
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Basically, fat tails was his passion throughout his whole life.
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Fat tails of everything, those spillovers of the River Nile,
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everything, rainfall, everything was fat tailed.
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So, [LAUGH] And he was right, I think, pretty much true.
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But that wasn't the motivation for
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the research that I was doing on markets basically and how they work.
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Economics of it, [COUGH] So
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that's where the joy hypothesis problem came up.
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And it's, [LAUGH] An unsolvable dilemma that you can't test market
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efficiency outside the context of some model that tells you what equilibrium
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expected returns look like.
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So you need a model of market equilibrium in order to test whether enterprises
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conform to that model so when you do the tests.
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It's always a joint test.
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You don't know what you're rejecting, whether you're rejecting a model of market
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equilibrium or whether you're rejecting market efficiency.
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So that's the conundrum that this insight poses.
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But as a student of Harry Roberts,
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what I learned was there's no real truth out there.
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You're basically just trying to improve your description of the world.
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There's nothing that's really truth top to bottom.
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So you try to learn a little bit every time we do something, but
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don't expect that you learn everything other care anywhere near 100%, right?
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Somebody's gonna come along and improve on what you do.
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Maybe it's you, maybe it's somebody else, but somebody will do it.
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>> Jon Hartley: I guess my understanding is sort of that hypothesis problems,
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it says that at some level,
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efficient capital marks is something that's difficult to test.
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But a lot of your work though is very empirical.
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And so I'm curious, how in your mind does you know your work on,
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say, looking at dividend buyback announcements and so forth?
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I mean, and seeing how prices respond immediately to these things.
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I mean, how do you think a lot of your work advance,
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your empirical work specifically kind of advance this idea of efficient markets?
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I guess maybe you've just seen that many of these
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events are sort of immediately incorporated into asset prices.
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>> Eugene Fama: Well, that part, farmer fisher,
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Denson Roll was the first event study.
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There have been thousands of them since then, but
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none of us had ever done another one.
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So the original four never did another event study,
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and now people do event studies.
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They don't even give us a reference anymore.
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It's so built into the literature.
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It's in macroeconomics, basically, everywhere.
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>> Jon Hartley: Applied economics everywhere.
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>> Eugene Fama: For example, it's a fundamental way that the law people
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try to establish precedence in law, so it's everywhere.
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And- >> Jon Hartley: As you say,
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they're used in court cases, event studies.
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I mean, it's amazing how influential it is not just in academia and
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academic research, but also in the real world.
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>> Eugene Fama: That's only half of it.
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So the other half is you have to have some statement about how prices get formed.
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You need a model of market equilibrium.
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And that's the other side of my research on asset markets is trying to come up with
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models of market equilibrium that help us describe expected returns better.
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Some of it worked well and some of it I was really confident in and
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it seemed to work in the US and around the world.
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Seems to have basically disappeared or gotten a lot weaker.
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Maybe we killed it in the process of developing it and
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investors jumping onto it, but who knows.
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But anyway, that was the other side of the story that I've
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worked on basically continuously.
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>> Jon Hartley: Good, totally, well, I wanna dive a little bit into, I guess,
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we'll talk about factors in a second here, but I wanna talk a little bit just
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about sort of efficient markets versus behavioral finance.
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And often I hear, when I've heard yourself and Richard Thaler who sort of an emissary
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that sort of behavioral finance school that when you've been together on
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panels that you generally agree on the facts but disagree on interpretation.
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And I think you maybe take more of a risk-based or a rational lens
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versus Thaler who takes more of say an irrational behavioral lens.
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I'm curious what you think about the legacy of efficient markets is and
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what you think the legacy of, say, behavioral variance is.
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I mean, there's been a massive rise in passive investing over the decades,
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which is a clear win for official markets obviously,
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DFA, BlackRock, Vanguard, all part of that.
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I mean, there's also these super successful quantitative
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hedge fund stories, Rentech, Shaw, some multimanager.
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Then one could just argue that they're taking advantage of information.
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It's a rational story there as well, and
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maybe only a small pool of investors can do that.
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They provide liquidity, all these things.
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Now, alpha is a zero sum game of beta, so they are doing active management that
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that outperformance has to come at the expense of some losers.
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But I guess separately, there are some investors out there that I guess use and
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hold up momentum and
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some claim that there's momentum factors, those like your student, Mark Carhart.
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And I think momentum is a pretty behavioral phenomenon.
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I mean maybe some people are you.
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There's momentum crashes, which are maybe compensated by risk.
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But how do you think about things like, say, the 1990s tech boom or bitcoin?
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I mean, are bubbles real?
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I'm just curious how you think about these things.
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>> Eugene Fama: Well, the way I think about them is you get to show me,
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you can't just tell me that the market's inefficient.
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So Taylor and I are great friends and I have been criticizing him for
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many years saying basically what you call behavioral finance,
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really just a criticism of efficient markets.
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You don't have a theory of your own.
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It's just a criticism.
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So I think you're just a branch of efficient markets, Julie,
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you're afraid to call yourself that.
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>> [LAUGH] >> Eugene Fama: So
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that he doesn't really take to that very well.
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But [LAUGH] the challenge comes, you can see Bob Schiller,
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who I admire a lot, and he basically came up with a fundamental
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insight that said prices are much more variable than
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you can explain if expected returns are constant.
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So you have to have a lot of variation in expected returns to explain
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the variation in stock returns.
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Okay, that's fine, but then you have to tell me that something in there is
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irrational, either the variation of expected returns or
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the deviation of returns from expected returns.
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And they haven't got that far and not got much far.
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So again, basically, it's all just a criticism of efficient markets.
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And okay, fine, you're a subbranch of efficient markets then.
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>> Jon Hartley: Yeah, I mean, and
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what you're referring to is Robert Schiller's observation that stock prices
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are much more volatile than the present discounted value exposed dividends.
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If you were to look back over the many, many decades or over the centuries and
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you were to take the future dividends with the benefit of hindsight and
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to discount them back using a discount rates would from that time.
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Why is that value more constant than the actual stock prices themselves?
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And maybe it's something that you're using the wrong
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discount rate, I guess, is- >> Eugene Fama: The discount rates
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are varying through time.
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>> Jon Hartley: Exactly.
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>> Eugene Fama: That's almost a tautology.
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You're saying, okay, that will do it, that's true.
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But then have you got a story about what makes discount rates expected
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returns rational or irrational.
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And that's something about, well,
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what are the limits of a rational model of equilibrium?
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And that one still is waiting out.
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We're still waiting for that one to get solved.
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Either on the efficient market side or the inefficient market side,
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nobody's coming up with that, a really convincing argument there.
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>> Jon Hartley: How do you think about these things, I guess,
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the 1990s tech boom or Bitcoin?
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I mean, these things are extremely- >> Eugene Fama: I
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have a problem with Bitcoin.
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I have a real problem there.
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>> Jon Hartley: But what's your problem with Bitcoin?
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>> Eugene Fama: Well, Bitcoin Is not a credible medium of exchange.
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My learning of macro of monetary economics basically said, if you're going to be
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the medium of exchange, you can't have a highly variable real value.
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And Bitcoin's real value is highly variable.
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So think of it as businesses don't want to do business in terms of a unit of account
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or a currency that's so highly variable it itself can knock them out of business.
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Don't want to do that.
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So you don't expect that a, a medium of exchange that's highly variable in terms
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of its real value, will survive.
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That's just classic monetary theory.
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So that's why bitcoin gives me a problem.
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So I'm basically hoping it'll crash, that it will be a bubble.
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But the problem with other bubbles is they turn out not to be.
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You have to have a somewhat strange definition of a bubble to identify them.
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So, for example, stock prices were supposedly to have been a bubble.
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And then it turns out they ended up,
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they eventually went higher than they did when they were called, when it was called.
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Who was the Fed governor?
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The Fed guy at the time that said they were a bumble anyway.
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But it turned out to be prices did go down, but
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then they went up much more than they had gone down.
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So at that point that's just a bundle.
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It's just the random variation in prices.
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>> Jon Hartley: It's so interesting because,
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I think 10 years ago there was a lot of promises that that Bitcoin
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was going to become more of a medium of exchange,
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that people would be using it to make payments regularly in the real economy.
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And that I think pretty obviously has not happened yet.
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So it, I think in some weird way it's an asset that doesn't have any cash flows and
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is just, you know, like in a sense a purely speculative asset where,
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you know, it's only sort of worth what other people believe it to be worth.
26:03
And obviously that can generate a lot of volatility if people's thoughts change.
26:08
But it's interesting that all these folks, you know,
26:11
some folks have said that it's an inflation sort of hedge.
26:14
And I don't think that's clear either because in fact it doesn't seem to
26:18
respond to bad.
26:19
>> Eugene Fama: Can't be an inflation hitch.
26:21
Can't be an inflation because variance is too high.
26:24
Inflation has very low variance.
26:26
>> Jon Hartley: Exactly.
26:27
So even when you get a negative inflation print,
26:30
it's not like bitcoin rallies in response to that.
26:34
But it seems to be very correlated with risk assets and stocks.
26:38
So it's almost like this pure risk asset in a sense.
26:42
So it's becoming something like that, based on this kind of idea that other
26:46
people will evaluate at something in the future.
26:50
All of crypto I think is interesting or
26:55
unique in this respect, and we'll see where it all goes.
27:02
But particularly, interesting same thing I think with other bubbles where there's,
27:08
I think, often something or what people would call bubbles.
27:12
You often see either massive technological advances that don't pan out or
27:17
you know, cases of fraud or other things like that.
27:21
I guess to be a bubble, you know,
27:23
you need a big, I guess contraction right after some big run up.
27:26
And so, I guess you think the 90s tech boom,
27:30
what happened there, a lot of projects.
27:34
>> Eugene Fama: They were going to contend that this wasn't a bubble in the sense
27:38
that enough companies survived that and got so extraordinarily big that that was
27:43
a good investment, but you just couldn't pick the winners.
27:46
That was the only problem.
27:48
But the activity itself, the idea that somebody was going to emerge from that
27:53
time that would have a very high valuation, that turned out to be true.
27:57
>> Jon Hartley: We now have the Mag 7 stocks or the main stocks, Facebook,
28:01
Amazon and.
28:02
Google and all these companies.
28:03
It came out of that era, I guess, not Facebook,
28:07
but Amazon, Google came out of that era.
28:10
I guess sort of the next question really is getting into factors.
28:15
And so I'm curious what you think about the so called factor zoo for
28:21
one, 10 years ago, finance researchers spent tons of
28:26
time researching asset pricing factors like size,
28:31
value, the market factor, some interesting momentum.
28:36
Obviously, the fama French Factors from your 1993 paper, Size,
28:39
Value in the market.
28:41
Now there's I think a lot of questions about this empirical asset pricing.
28:45
It's much harder to publish I think papers about factors and I think there's
28:51
questions about the persistence of factors after they're published.
28:56
Size factors haven't worked as well in recent decades.
28:59
The same with value.
29:00
I think this has created a lot of challenges for value based managers,
29:03
I think and there's some questions about sort of replicability or maybe if,
29:08
if a factor is published it gets arbitraged away.
29:11
I'm curious, what do you think about that and
29:14
just the legacy of I guess the fama French factors from your 1993 paper.
29:19
You have a more recent paper that you wrote in the 2010s that offers
29:22
five factors.
29:23
I'm curious what you think about this concept of
29:28
factors to describe the behavior of stock prices.
29:33
>> Eugene Fama: When French and I got into this, basically we said from the beginning
29:38
that we have to look and make sure they're robust.
29:41
Did you see them not only in the US for a particular period, did you see them in
29:46
the US for periods outside the period that you use to identify them?
29:50
And then, you look around the world and see if you see them other markers.
29:55
And that was the approach we always followed.
29:57
So first we would expand the data in the US and then we would look
30:02
outside the US and we only would kind of concentrate something and
30:07
see it was a real factor if it survived all those tests.
30:12
And that was fine.
30:13
But we also said, you know, that once you get past the market factor,
30:18
these specialized, more specialized factors have to have something else in
30:23
them that causes people to be afraid of them and to let move in that direction.
30:28
And if people only are afraid of them, they can kill them.
30:31
They can kill these expected returns associated with these factors.
30:35
So we said that from the very beginning and
30:38
there's some chance that that's what actually happened.
30:41
So we found the size factor, the value factor, and
30:44
people weren't afraid of small stocks.
30:47
Turned out they weren't afraid of value stocks.
30:50
So maybe they killed it.
30:52
I don't know.
30:53
I mean the problem is that these factors are buried in so
30:57
much variance you can't tell whether they gone or not.
31:00
So it's going to take another 50 years to come up with the right answer and
31:05
I won't be alive then.
31:07
So we won't know.
31:09
>> Jon Hartley: Well, you know, I know that.
31:12
What's amazing, I mean, just to think too, I mean we have,
31:16
I guess centuries of data now.
31:19
I mean some people have tried to take the CRSP data and go back further.
31:23
I mean, were you a part of the found the creation of CRSP, the Center for
31:26
Research and Security Prices?
31:28
I know that that's I guess one of the earlier sort of ideas or
31:34
efforts to compile a lot of asset data.
31:38
And that's been housed at the University of Chicago for a long period of time.
31:41
I mean to do early research, pre personal computers, I'm sure you
31:46
had to do a lot of work to even just get stock price data in those days.
31:52
People were looking to newspapers still to look up stock price quotes often.
31:58
I'm, Curious, how did that evolution work in terms
32:04
of- Okay, I was there so I can tell you that one.
32:08
>> Eugene Fama: [COUGH] Larry Fisher developed the NYSE tapes first
32:12
at the University of Chicago, but they weren't ready when I
32:15
was ready to write my thesis, they weren't even close to being ready.
32:20
[COUGH] So I had data that I had collected as an undergraduate at Tufts on
32:25
the 30 Dow Jones Industrials.
32:27
So that was the data that I used in my thesis to develop [COUGH] both
32:32
the fat-tailed distribution stuff and the efficient markets stuff.
32:37
So I didn't use the CRSP data at all at that point.
32:44
And then the CRSP tapes came along and the research in that area exploded.
32:49
But I'm not sure, was that your full question or did I miss some?
32:54
>> Jon Hartley: No, that's it.
32:55
I mean, it's just, it's amazing.
32:56
I think people don't appreciate, I mean, now everyone has computers and
33:00
access to high-frequency data.
33:01
>> Eugene Fama: Well, you're right, that's the other problem.
33:04
So when I was even with the Dow Jones Industrials,
33:08
you're dealing with a machine that can test
33:13
problems with any reasonable amounts of data.
33:17
You're sticking cards into this machine to, to put it there.
33:21
And I used to go over in the middle of the night into the computation center and
33:26
do my work cuz there was nobody there at that time.
33:29
Me and another guy in the physics departments were the only ones there that
33:34
we could have access to this machine that could do almost nothing [LAUGH] and
33:40
fill the whole room.
33:41
[LAUGH] But anyway,
33:42
that's what I use with these 30 Dow Jones Industrials to do my thesis.
33:47
And so I work from it.
33:50
>> Jon Hartley: That's amazing.
33:51
And yeah, just to think how just empirical research has exploded since then.
33:59
And I guess I'm curious just to, I guess, get back to this question
34:04
of sort of factors and thinking about the structure of asset prices.
34:09
So one, I mean, there's been a massive outperformance in the market factor,
34:15
especially in US equity markets in sort of the past decade or
34:19
since the financial crisis.
34:22
Whereas other advanced economy equity markets have been generally flat for
34:27
the past decade or so comparatively.
34:30
And maybe that's because GDP per capita
34:34
has also flatlined in these sorts of countries.
34:38
I mean, do you have any thoughts on the equity risk premium or why it's been so
34:43
large compared to other countries?
34:45
I mean, there's some people out there who say, well, quantitative easing
34:49
is a big part of the story and the Fed wasn't doing that before 2008.
34:53
But what I would also say, would challenge people when people say that
34:58
QE is responsible for the massive run up in the stock market and
35:02
causing things like wealth inequality, so forth.
35:06
I mean, other central banks around the world, the ECB, the Bank of Japan,
35:10
they were doing just as much quantitative easing as a fraction of GDP as
35:14
the Federal Reserve.
35:15
So I don't really think that the story is QE either.
35:19
I mean, the Fed buys a bond and also issues reserves, and
35:23
maybe it's just sort of a wash as a result of that.
35:26
But I'm curious, this massive outperformance of the US equities,
35:31
is that really a growth story in your mind or
35:34
do you have any other thoughts- >> Eugene Fama: I think it's just a growth
35:38
story, right, the fact that the US won on the growth story in that period of time.
35:44
Europe that had been doing very well, Japan that had been doing very well,
35:48
didn't do so well in that period economically.
35:50
So stock returns are the basically highly
35:55
leveraged claim on the output of the country.
36:00
That's the explanation as far as I'm concerned, as far as I know.
36:04
>> Jon Hartley: It's just amazing to think, I mean, the idea that there would
36:08
be so much divergence between the US and other advanced economy countries.
36:13
I mean economists, macroeconomists for a long time talked about
36:17
divergence in general, which is really richer countries,
36:22
advanced economy countries getting richer while poor countries that presumably
36:28
could import the same technology and the same ideas weren't catching up.
36:34
And there's some degree of evidence that there's been
36:37
a convergence across all countries in, say, the 90s and 2000s.
36:42
I think since COVID, growth rates have gone back a bit.
36:45
But I think there's this kind of new type of divergence that we're seeing,
36:49
which is just there's the US and everybody else and all the other countries.
36:52
And I think a lot of that might have to do with technology, why most of
36:57
the largest technology companies in the world are all based in the US.
37:02
And there's some story there, maybe it's a long run institution story,
37:07
that the US always been a very good place to do business or
37:10
that these entrepreneurs came a long time ago and sourced at the seed and
37:14
now all the top talent from around the world wants to come to the US.
37:18
I mean, do you have any sort of macro thoughts on why the US has kinda won
37:23
this race, if you will?
37:25
>> Eugene Fama: Well, that's a good one.
37:26
We've imported lots of high-end people in the tech industries that have been
37:32
instrumental in developing all these firms that have become massively profitable.
37:39
I don't know if you have to go any further than that.
37:41
So the talent wants to come here.
37:44
If we can keep it that way, we'll be happy.
37:47
>> Jon Hartley: Yeah, I want to talk about some newer theories that I think try and
37:53
challenge efficient markets a little bit.
37:57
And it's interesting because we're talking a lot about the 1960s and
38:03
what the prevailing sort of theories were about what moved asset prices prior to
38:08
the advent of modern finance, which is, you've been a central part of developing.
38:14
A lot of that has to do with the role of information,
38:19
expected future dividends, expected returns.
38:25
>> Jon Hartley: And obviously equilibrium, no arbitrage,
38:29
all these things playing a big role in that.
38:32
But what's interesting is prior to the 1960s,
38:37
my understanding is that there was a big emphasis on supply and
38:42
demand curves kind of determining stock prices.
38:46
And what's interesting is I think some of those ideas have come back, and
38:51
there's a big debate right now about the slope of the demand curve for stocks.
38:56
And of course, if markets were perfectly informationally efficient,
39:01
I think the demand curve for stocks is perfectly elastic or
39:04
the demand curve is essentially totally horizontal.
39:07
>> Eugene Fama: I don't so.
39:09
>> Jon Hartley: You don't think so?
39:10
>> Eugene Fama: No, of course not.
39:12
[LAUGH] Stock market is no different from any other market.
39:19
If resources pour into it and push prices up,
39:22
expected returns are gonna go down rather than other forms of investment.
39:27
So it can't be perfectly flat.
39:31
It's part of the overall, that the wealth in the world is limited, and
39:35
if more of it goes into one asset than another,
39:38
that asset's price gets bid up and its expected return goes down.
39:42
So it can't be perfectly horizontal, not at the level of the entire market.
39:48
>> Jon Hartley: I mean, well, it's interesting because I think behavioral
39:53
finance researchers, for example, like Andre Shleifer,
39:57
he wrote a famous paper in the 1980s that Titled yet
40:02
does the demand for stock slope down?
40:04
And, you know, that is what happens if there's, you know, some flow, some
40:09
exogenous flow into the stock market from, say, you know, a big index rebalance,
40:14
like, you know, the Russell 2000, it reconstitutes once a year.
40:18
And he looked at these index adjustment or index reconstitutions,
40:24
like the Russell 2000 ads, takes out companies that have
40:29
changed in their size over the year and they add a new one.
40:34
They do it on a certain date.
40:35
And that causes lots of flows from index funds in and out of certain stocks.
40:41
And, you know, you looked at these stocks and argued, you know,
40:45
there's a reaction in stock prices in that clearly quantities matter.
40:49
And then he concludes that the demand curve for for stock prices,
40:53
do slope down, but just a bit, these demand curves are still elastic.
40:59
And we'll talk about what that kind of means.
41:01
But in part what it means is that a elastic means that, you know, a $1 billion
41:07
flow would lead to a less than $1 billion change in, say, the market cap of stocks.
41:13
And I'm curious what you think about some of this even newer research on quantities,
41:17
like, for example, you know, this new area called demand based asset pricing.
41:22
A lot of it's led by Ralph Koijen, who's a finance colleague of yours at Booth,
41:26
part of his research agenda, he also has this paper with Xavier Gabaix that's
41:30
titled the Inelastic Markets Hypothesis.
41:33
And we've spent some time talking about this paper before.
41:37
And they essentially claim that the demand curves for
41:39
stocks are even more downward sloping, that they're very downward sloping.
41:43
And they claim that a $1 billion inflow into the stock
41:49
market will cause a $5 billion appreciation approximately in market cap,
41:56
that stocks, at the macro level, are very responsive to flows.
42:03
And in part what they're trying to do is sort of get at the origins of financial
42:07
fluctuation, what's causing financial fluctuations.
42:10
So what they claim is that it's really quantities, I think, that are really
42:15
driving fluctuations in asset prices, I think less than just information.
42:20
But I'm curious what you think about all this research that claims that quantities
42:25
matter just a ton for stock, for stock market prices in determining them.
42:30
And I think at some level it's a bit of an affront to modern finance and
42:35
trying to go back to this era prior to modern finance, which obviously
42:40
plays a huge role on information equilibrium, no arbitrage and so forth.
42:46
>> Eugene Fama: I'M not that familiar with that research.
42:49
So I mean it comes down to are these, are these effect permanent?
42:54
Are these effects permanent or transitory?
42:56
So it's just a matter of trading pushes' prices around temporarily.
43:02
That's, that's testable.
43:04
There should be some part of the variance of the prices
43:08
that's temporary that you can get out of, get around.
43:13
And there should be trading opportunities for
43:15
people who want to take advantage of this as well.
43:18
So it better be permanent,
43:19
otherwise it gives rise to lots of profit opportunities.
43:23
But I haven't followed it that closely, so I can't really comment on this.
43:28
>> Jon Hartley: I do think that.
43:30
So my understanding is that the inelastic markets hypothesis does claim that these
43:34
effects are permanent.
43:35
That a $1 billion flow into say the equity market, say someone takes money out of
43:39
bonds or, or just they have a billion dollars in cash and in their bank account
43:43
and they, they put that billion dollars, you know, it could be a corporation or
43:48
have you, or investment manager, they put that money into the stock market.
43:52
They say that that's gonna lead to a $5 billion appreciation in the total
43:56
market cap.
44:01
>> Eugene Fama: That's possible.
44:02
You know, when you said earlier that the demand curves were flat,
44:07
we don't really know how elastic they are at the aggregate level when you're
44:12
looking at the total shifts of total wealth between different asset classes.
44:17
So we don't know what the effects are.
44:19
And I think that's what Ralph is working on there.
44:22
I'll have to go back and read that stuff a little more carefully.
44:26
It's not that easy for me, but I'll do it.
44:30
>> Jon Hartley: Yeah, well, it's very interesting I think, and
44:34
they look at things like flows into US equity markets.
44:39
And I think that there's, I think some challenges too in terms of, you know.
44:42
Well, you know, what's driving those flows to begin with.
44:45
Right. Are they truly exogenous or is it just,
44:47
you know, this great US stock market run up that we've seen,
44:50
is that what's maybe causing the quantity in the first place?
44:54
So I think it's a little hard to disentangle the two.
44:57
And they use other strategies like granular instrumental variables and
45:01
so forth.
45:01
I sort of have my own paper on this.
45:04
It's sort of a tongue in cheek titled the Elastic Markets Hypothesis, is sort of
45:08
using country equity index additions and deletions for identification.
45:12
So you have big index funds which from time to time will have to
45:17
take their money out of a certain country or put money into a country,
45:23
say the MSCI Emerging Markets Index, say, promotes a country into its index.
45:30
And there's billions of dollars, or if not trillions of dollars that follow,
45:35
that kind of an index, and using those for identification.
45:39
So I mean, we don't really find that, you know, that prices are all that
45:44
responsive to, to, to clients, but, but, but that there is some response.
45:50
And typically it's a bit more transitory and temporary than,
45:54
than something that would be a permanent change.
45:57
But what's interesting too is like, I think in the practitioner lens,
46:03
there's a lot of these rules of thumb, like the quadratic rule
46:09
when we think about things like transaction costs, for example,
46:14
say you have some purchase of stocks, that it follows this three
46:19
halves function in terms of the market impact of a purchase.
46:25
When investment managers are trying to think about what the impact of their own
46:30
trades are, they use this model to sort of assume that going
46:33
into the market actually buying some stocks will have some effect.
46:39
They measure it, I think, pretty regularly using the sort of three-halves,
46:43
this kind of quadratic type rule.
46:45
But I think it's very much a transitory thing.
46:47
I don't know. Have you ever thought too much about say,
46:50
transaction costs and things of that nature, as maybe more of a practitioner?
46:54
>> Eugene Fama: I know, for example, that at Dimensional they've always been very
46:59
concerned about the effects of trading on prices,
47:02
especially when they were in a small stock business.
47:05
But they could never really find that there were lots of strong
47:10
temporary effects.
47:12
In all the research that was done there, they never could find that.
47:17
I never delved into it very much.
47:20
They have a whole crew of PhDs that do this kind of stuff for them.
47:26
But I was pretty well convinced that they were finding that the prices were,
47:30
at least for individual stocks, were pretty elastic.
47:34
They weren't that responsive to magnitudes of money going into them.
47:40
>> Jon Hartley: Yeah, and I think that's right.
47:42
I think, I do think that markets are pretty elastic and
47:46
there's lots of active managers that are trying to look at moments
47:51
where things are, maybe there's a bit of market impact from say,
47:56
some sort of a flow, or maybe there's these things like the.
48:01
Lipper a fund data that tracks mutual fund flows and
48:05
this data comes out pretty regularly.
48:08
I know a good number of bond traders sort of follow these sorts of things or
48:13
think about like month end effects for example,
48:17
like all the bond indices reconstitute at the last day of every month.
48:22
There's a paper I wrote with a co author on how prices, how treasury typically
48:27
rally on the last day of the month just because there's all these newly issued
48:33
Treasuries that don't enter the big bond indices until the last day of the month.
48:39
It's the same thing with stocks.
48:41
And typically a lot of rebalancing happens at the end of the quarter.
48:46
And so if there's big fund flows and maybe there's some
48:50
empirical finding that there's a jump in prices along those days but
48:54
typically, these things aren't that long lasting, they're temporary.
48:59
And so the extent that they exist,
49:01
sure demand curves slope down a little bit but not too much.
49:06
And I think I agree with you there on demand curves being fairly elastic but
49:12
not perfectly elastic.
49:14
And two, I think it's possible that efficiency is saying something really
49:19
different which is saying something more about how information gets incorporated
49:25
and that's, that's different from, from, from demand too in quantities.
49:30
I think those things are, are a little bit different.
49:34
>> Eugene Fama: Miller always said, when information comes into the market,
49:38
they didn't even be any trading and
49:41
prices adjust just the best bid ask prices adjust.
49:44
So it doesn't really take trading to do it turns out it does take some trading to,
49:49
to do it as it turns out.
49:51
But you know, the information effects and price pressure effects because
49:55
relative demand shifts for different asset classes are two different things.
50:01
These are those two different things, one's kind of a micro thing and
50:04
the other is a macro thing.
50:06
So the macro thing is I think with Ralph and
50:09
Gabe are Interested in and that one is an open issue.
50:13
I think we don't really know the answer there.
50:15
They think they have it.
50:17
They're sure to attract people that will try to substantiate what they're claiming.
50:24
So we'll, we'll see about that one.
50:28
>> Jon Hartley: And other folks that may find the contrary as well and
50:31
maybe that's really kind of the new efficient markets versus behavioral
50:36
finance kind of a debate going forward.
50:39
>> Eugene Fama: That isn't though that's just relative demand.
50:42
Give me shifts in relative demand for different asset classes.
50:46
You can have price effects.
50:47
How big they are is the issue.
50:50
They could be big, they could be small.
50:51
I really don't know the answer.
50:54
>> Jon Hartley: That's a great point.
50:55
I'm curious, one last question, I guess on just intermediaries and intermediary.
51:02
Asset pricing has been I think a big new kind of area of research or
51:06
renewed area research in the, I think years after the financial crisis.
51:11
A lot of great researchers and
51:13
potential economists I think have turned their attention to this.
51:18
I think of folks like Daryl Duffy, Arvin Christian Murthy and at Bismuth Jordan and
51:23
many others who are particularly interested in the effects of thinking
51:28
about things like fire sales that we saw maybe during the financial crisis and
51:33
who is the marginal investor?
51:35
Who is, who's really determining asset prices and
51:41
there's a whole, who's pricing on their kernel and so forth.
51:47
I'm curious what you think about that sort of strand of literature and how you think
51:53
about intermediaries and in your mind does the marginal investor matter in
51:58
the determination of asset prices or is everyone the marginal investor?
52:03
I'm curious, how do you think about all that?
52:05
>> Eugene Fama: I think everyone is a marginal investor.
52:08
I'm concerned because everybody is,
52:10
everybody's holding the stock is basically deciding instant by instant implicitly or
52:16
explicitly to continue holding based on the prices or any assets.
52:20
So everybody's a module investor as far as I'm concerned,
52:24
I don't really relate very well to that literature.
52:28
>> Jon Hartley: And even I guess a retail investor or so called passive investor,
52:33
you don't think that they're maybe less attentive or, and
52:37
that that would really matter or I guess that's a different issue.
52:42
>> Eugene Fama: We can't have 100% passive investing, that's for sure.
52:45
There has to be somebody out there that's concerned about the prices being right and
52:50
there's somebody who makes money based on doing that.
52:53
Otherwise you're not going to get an efficient market.
52:55
You know, that's market can't be efficient for everybody sufficient for me.
53:00
Maybe it's efficient for you but
53:02
there have to be some knowledgeable investors out there.
53:05
So for example, insiders trading the stocks of their company,
53:08
they have inside information that's been well established.
53:12
But otherwise, you know, then they're also, I think now Ken French and
53:17
I have a paper on mutual fund investing where we try to identify how much
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information there is out there that the mutual funds capitalize on.
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If you give them back all the money that they spend, fees and expenses,
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then you can see that there are winners and there are losers and
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they're that they deviate from what you would expect by pure chance if none
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of them had any special information.
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And that, that's fine.
53:43
I mean, they're helping to make the market more efficient.
53:46
But.
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>> Jon Hartley: And I think that's the kind of maybe the insider, but
53:54
I guess Grossman, Siglitz, and I guess the idea is that there always is some
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a bit of alpha out there and that generates these,
54:02
there's always people seeking this little bit of alpha and
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that there always has to be a little bit in order to make markets efficient.
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>> Eugene Fama: Right.
54:12
You know, the, the, the question always arises,
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how much of that do you need to make it work?
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And the answer is, well, depends on how many bad guys there are out there,
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how many disinformed investors are out there,
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because they're the ones you have to offset.
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So you need fewer active investors.
54:32
If you, if all the disinformed guys become passive investors, one guy,
54:38
one belligerent active investor might be enough if all the bad ones drop out.
54:45
But we'll never know.
54:48
>> Jon Hartley: Well, Gene, this has been an amazing conversation,
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I really wanna thank you for coming on.
54:51
It's been a real delight to talk about your career and ideas and
54:56
really just this set of ideas that really began at the University of Chicago,
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which you largely led in establishing modern finance.
55:06
Really want to thank you for coming on.
55:07
This has been a truly amazing conversation.
55:10
>> Eugene Fama: My pleasure.
55:11
>> Jon Hartley: This is the Capitalism and Freedom in the 21st Century podcast,
55:14
an official podcast of the Hoover Economic Policy Working Group where we talk
55:17
about economics, markets and politics policy.
55:19
I'm Jon Hartley, your host, thanks so much for joining us.